Existing non-invasive methods for monitoring cardiovascular disorders utilize blood pressure (see for example U.S. Pat. Nos. 5,961,467, 4,669,485, 5,365,924, 6,135,966, 5,634,467, 5,178,151). However, clinical studies have provided indications that changes in retinal vasculature (e.g., narrowing of retinal arterioles and widening of retinal venules) may be an early indicator of cardiovascular disease (CVD) and other conditions, such as hypertension and diabetes. The conditions of retinal arterioles and venules reflect the conditions of the blood vessels in the rest of the body. The ability to quantify the characteristics of retinal vessels is important to determine the severity of retinal arteriolar narrowing and other conditions.
Arterioles and venules are small branches of the main retinal arteries and veins respectively and their condition is indicative of the smaller blood vessels in the body. Measuring the diameter or widths of the arterioles and venules from detailed digital retinal images and calculating the arteriolar-to-venular diameter ratio (AVR) is one method of quantifying the imbalance between retinal arteriolar and venular calibre size. This measure can vary with different retinal vessels taken into calculation. More importantly, AVR provides information only on one aspect of retinal vascular change, namely retinal vessel calibre, and does not take into account the many structural alterations in the retinal vasculature. However, it is difficult to quantify the above characteristics of retinal vessels on a large scale as the process would involve repeated measurements of the diameters of the arterioles and venules in the retinal images by trained human graders. This is labour intensive and the results can vary when different human graders are used. For that reason, to our knowledge, no platform presently exists for non-invasive observation of cardiovascular orders using retinal image analysis.
It is also known that the branching patterns of retinal arterial and venous systems have fractal characteristics. A fractal is a geometrical pattern comprised of smaller parts or units which resemble the larger whole. Fractals have been used to characterise diverse natural shapes such as the branching patterns of trees, the shapes of coastlines, the pattern of electrocardiograph tracings as well as retinal microcirculation. The fractal (or fractional) dimension (D) is one measure associated with fractals and has a range of definitions. However, it can be considered as a statistical quantity that provides an indication of how completely a fractal appears to fill the space occupied by the fractal as finer and finer scales are zoomed in upon. In other words, the fractal dimension can be considered as the number of smaller units comprising the larger unit that fit into that larger unit. The fractal dimension is always smaller than the number of dimensions in which the fractal being considered exists.
It was suggested in Patton N, Aslam T, MacGillivray T, Pattie A, Deary I J, Dhillon B., Retinal vascular image analysis as a potential screening tool for cerebrovascular disease: a rationale based on homology between cerebral and retinal microvasculatures. J. Anat. 2005; 206:319-348, that fractals offer a natural, global, comprehensive description of the retinal vascular tree because they take into account both the changes in retinal vessel calibre and changes in branching patterns.
In Mainster M. A., The fractal properties of retinal vessels: embryological and clinical implications, Eye, 1990, 4 (Pt 1):235-241, the analysis of digitised fluorescein angiogram collages revealed that retinal arterial and venous patterns have fractal dimensions of 1.63±0.05 and 1.71±0.07 respectively, which is consistent with the 1.68±0.05 dimension known from diffusion limited aggregation.
In Daxer A, The fractal geometry of proliferative diabetic retinopathy: implications for the diagnosis and the process of retinal vasculogenesis. Curr Eye Res. 1993; 12:1103-1109, retinal vessel patterns with neovascularisation at or near the optic disc (NVD) were compared with the vascular patterns of normal eyes. The presence of NVD in an eye is a high risk characteristic for severe visual loss requiring laser treatment. Fractal dimensions were calculated from digitised photographs using a density-density correlation function method. The mean fractal dimension D for vessel patterns with NVD was significantly higher (D=1.845±0.056) compared with the control group (D=1.708±0.073). A cut-off value for the fractal dimension is suggested to be 1.8, with higher values being potentially indicative of proliferative changes.
Hence, fractal geometry provides a global and more accurate description of the anatomy of the eye than classical geometry. Fractal patterns characterise how vascular patterns span the retina and can therefore provide information about the relationship between vascular patterns and retinal disease.